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Modeling loudspeakers based on cascading lumped parameter models with neural networks

a loudspeaker and neural network technology, applied in the field of loudspeaker systems, can solve the problems of unsuitable conventional design approaches, prohibitive time required to simulate different aspects of loudspeaker behavior using such techniques, and reduce the accuracy of a given lumped parameter model, so as to achieve efficient and accurate simulation of nonlinear aspects of loudspeaker systems, efficient and accurate

Active Publication Date: 2016-11-03
HARMAN INT IND INC
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

The patent text explains a technique that allows for better simulation of the nonlinear aspects of loudspeakers. This is done by using a neural lumped parameter model that combines the strengths of both models and compensates for their weaknesses. This results in a more comprehensive and accurate model of the loudspeaker system.

Problems solved by technology

However, the accuracy of a given lumped parameter model is reduced by the inaccuracies inherent in the simplifying assumptions made in the lumped parameter model as well as by any inaccuracies inherent in the values of the parameters used in the lumped parameter model.
While the tradeoff between efficiency and accuracy that is exhibited by a lumped parameter model is oftentimes understood and accepted, some aspects of actual loudspeaker behavior (e.g., breakup modes) are not adequately represented by a lumped parameter model and therefore need to be addressed by designers in some other way.
While such techniques provide more accurate insight into the behavior of loudspeakers, the time required to simulate different aspects of loudspeaker behavior using such techniques can be prohibitive and therefore unsuitable for conventional design approaches.

Method used

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  • Modeling loudspeakers based on cascading lumped parameter models with neural networks
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  • Modeling loudspeakers based on cascading lumped parameter models with neural networks

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Embodiment Construction

[0018]In the following description, numerous specific details are set forth to provide a more thorough understanding of the present invention. However, it will be apparent to one of skill in the art that the present invention may be practiced without one or more of these specific details.

Loudspeaker Characterization System

[0019]FIG. 1 illustrates a loudspeaker characterization system 100 configured to implement one or more aspects of the various embodiments. As shown, the loudspeaker characterization system 100 includes, without limitation, a loudspeaker 120, a sensor 130 and a loudspeaker modeling subsystem 140.

[0020]The loudspeaker 120 transforms an audio input 110 (i.e., an electrical audio signal) into a loudspeaker output pressure 125 to generate sound. The loudspeaker 120 may be implemented in any technically feasible fashion. For example, and without limitation, in some embodiments the loudspeaker 120 may be a “horn” loudspeaker. Alternatively, and without limitation, in some...

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Abstract

In one embodiment of the present invention, a loudspeaker modeling subsystem configures a neural lumped parameter loudspeaker (NeLP) model to represent the behavior of a loudspeaker. The NeLP model is implemented as a cascaded combination of a lumped parameter model (LPM) and a neural network (NN) model. To configure the model, the loudspeaker modeling subsystem first estimates values for the parameters used in the LPM. The loudspeaker modeling subsystem then “fixes” these parameters and trains the NN model to act on a predicted output pressure that is generated via the LPM. More specifically, the loudspeaker modeling subsystem configures the NN to modify the predicted output pressure to minimize the error between the predicted output pressure and a measured loudspeaker output pressure. Notably, by strategically fusing the LPM and the NN model, the NeLP model leverages the strengths and mitigates the weaknesses typically associated with conventional loudspeaker modeling techniques.

Description

BACKGROUND[0001]1. Field of the Invention[0002]Embodiments of the present invention relate generally to loudspeaker systems and, more specifically, to modeling loudspeakers based on cascading lumped parameter models with neural networks.[0003]2. Description of the Related Art[0004]Modeling the behavior of one or more loudspeakers is a typical step when analyzing and / or designing an audio system. For example, a designer may perform several computer simulations of a loudspeaker based on a model of the loudspeaker to better understand the behavior and characteristics of the loudspeaker within the overall audio system being analyzed and / or designed.[0005]One well-known type of model that is oftentimes employed when running such computer simulations is the lumped parameter model. In general, a lumped parameter model of a loudspeaker includes values of a set of parameters that, together, approximate the behavior of the loudspeaker. The parameters and the values of those parameters used in...

Claims

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Application Information

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IPC IPC(8): H04R29/00
CPCH04R29/001H03G11/00H04R3/007
Inventor IYER, AJAY
Owner HARMAN INT IND INC
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